Human reliability in manual assembly systems: a Systematic Literature Review

Pasquale, Valentina Di; Miranda, Salvatore; Neumann, Patrick; Setayesh, Azin

doi:10.32920/21280020.v1

Cited by 3 publications

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“…An extension of work originally presented at an international conference on Industry 4.0 and smart manufacturing is presented [8]. The systematic literature review method followed by [8][9][10][11] has been used, with updates and extension provided using recently published papers aiming to show the recent uses of DT models in production, predictive maintenance, and after-sales services. The following questions are answered: What is the current state-of-the-art on the use of DT models in industrial operations mainly in production, predictive maintenance, and after-sale services?…”

Section: Methodsmentioning

confidence: 99%

Digital Twin models in industrial operations: State‐of‐the‐art and future research directions

Melesse

Pasquale

Riemma

2021

IET Collab Intel Manufact

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A Digital Twin is a virtual representation of a physical product, asset, process, system, or service that allows us to understand, predict, and optimise their performance for better business outcomes. Recently, the use of Digital Twin in industrial operations has attracted the attention of many scholars and industrial sectors. Despite this, there is still a need to identify its value in industrial operations mainly in production, predictive maintenance, and after-sales services. Similarly, the implementation of a Digital Twin still faces many challenges. In response, a systematic literature review and analysis of 41 papers published between 2016 and 11 July 2020 have been carried out to examine recently published works in the field. Future research directions in the area are also highlighted. The result reveals that, regardless of the challenges, the role of Digital Twin in the advancement of industrial operations, especially production and predictive maintenance is highly significant. However, its role in after-sales services remains limited. Insights are offered for research scholars, companies, and practitioners to understand the current state-of-the-art and challenges, and to indicate future research possibilities in the field. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Section: Methodsmentioning

confidence: 99%

Digital Twin models in industrial operations: State‐of‐the‐art and future research directions

Melesse

Pasquale

Riemma

2021

IET Collab Intel Manufact

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“…However, so far, much of the work of HF/E specialists, to analyze the origins of error‐related quality deficiencies, has focused on improving the immediate human‐system interface and relatively less on broader organizational factors. Evidence of this can be found in several recent studies where the human reliability analysis (HRA) approach was used to identify and quantify assembly errors (Blackert et al, 2019; Böllhoff et al, 2016; Caputo et al, 2017; Pasquale et al, 2018; Torres et al, 2021a). As a result, more recent systems thinking‐based risk assessment methods have been given less consideration when analyzing error‐related quality deficiencies in manufacturing environments.…”

Section: Introductionmentioning

confidence: 99%

Applying AcciMap and STAMP to the analysis of human error in complex manual assembly

Torres

Nadeau

Landau

2022

Hum Ftrs & Erg Mfg Svc

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In sectors such as aerospace manufacturing, human errors in the assembly of complex products can negatively impact quality, productivity, and safety. Until now, the analysis of assembly errors has focused more on the immediate human‐system interface and less on broader organizational factors. This article presents a case study‐based analysis of assembly errors in the aeronautical industry using the systemic methods AcciMap and Systems‐Theoretic Accident Model and Processes (STAMP). We seek to provide the company with elements to build a quality improvement strategy that considers human factors and ergonomics from a systemic perspective. The data and information necessary to conduct the analysis came from a project carried out at an aerospace manufacturing facility over a period of 12 months. The team had direct and recurrent access to primary data sources and communication with various stakeholders. A total of 31 influencing factors were identified with AcciMap at different levels within the manufacturing system. STAMP made it possible to model the sociotechnical control structure of the assembly process and identify several control flaws leading to hazards. The analysis shows that systemic methods require a high level of understanding of the manufacturing system and access to relatively high amounts of data and information. Therefore, direct contact with the field and stakeholders is crucial. Training quality specialists on systemic methods could support its use and help to close the gap between theory and practice. Globally, the field of quality in manufacturing could benefit from using systemic methods when deemed necessary.

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“…The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/0144-5154.htm (Griffith and Mahadevan, 2011;Di Pasquale et al, 2018;Su et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of failure risks for manual tightening operations in automotive assembly lines

Altinisik¹,

Yildirim

Topçu

2022

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Purpose The tightening operations are one of the most critical operations in automotive assembly lines because of its direct impact on customer safety. This study aims to evaluate the major complexity drivers for manual tightening operations, correlate with real tightening failure data and propose mitigations to improve the complexity. Design/methodology/approach In the first stage, the complexity drivers for manual tightening operations were identified. Then, the relative importance of the risk attributes was defined by using pairwise comparisons questionnaire. Further, failure mode effect analysis–analytic hierarchy process (FMEA–AHP) and AHP ratings methods were applied to 20 manual tightening operations in automotive assembly lines. Finally, the similarities between the revealed results and the real failure rates of a Turkish automotive factory were examined and a sensitivity analysis was conducted. Findings The correlation between the proposed methods and manual tightening failure data was calculated as 83%–86%. On the other hand, the correlation between FMEA–AHP and AHP ratings was found as 92%. Poor ergonomics, operator competency and training, operator concentration-loose attention fatigue, manual mouthing before the tightening operation, frequent task changes, critical tightening sequence, positioning of the part and/or directional assembly were found relatively critical for the selected 20 tightening operations. Originality/value This is a unique study for the evaluation of the attributes for manual tightening complexity in automotive assembly lines. The output of this study can be used to improve manual tightening failures in manual assembly lines and to create low complexity assembly lines in new model launches.

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Human reliability in manual assembly systems: a Systematic Literature Review

Cited by 3 publications

References 0 publications

Digital Twin models in industrial operations: State‐of‐the‐art and future research directions

Digital Twin models in industrial operations: State‐of‐the‐art and future research directions

Applying AcciMap and STAMP to the analysis of human error in complex manual assembly

Evaluation of failure risks for manual tightening operations in automotive assembly lines

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